Why the study?
Investigating patch-wise aortic wall shear stress differences between cohorts requires methods that address the multiplicity of testing.
Do permutation tests with TFCE improve the identification of regional wall shear stress differences in patients with mild-to-moderate aortic dilation compared to standard statistical tests?
Do permutation tests with TFCE improve the identification of regional wall shear stress differences in patients with mild-to-moderate aortic dilation compared to standard statistical tests?
Permutation tests applied to 4D Flow MRI data effectively identify regional wall shear stress differences in aortic dilation while appropriately correcting for multiple comparisons and spatial relationships.
Permutation tests enable reliable patch-wise aortic WSS comparisons; leaves open validation before clinical or research adoption.
BACKGROUND: Aortic wall shear stress (WSS) maps allow three-dimensional visualization and quantification of WSS patterns in the aorta and can be used to identify patch-wise differences between cohorts. However, a method addressing the multiplicity of the testing should be considered when investigating patch-wise differences. In this study, we sought to explore the capability of permutation tests in addressing the regional statistical differences in WSS values between patients with mild-to-moderate aortic dilation with tricuspid valves and age- and sex- matched controls. METHODS: 4D Flow MRI-derived WSS parameters were computed in a cohort of 46 patients with mild-to-moderate ascending aortic dilation ("cases") and a cohort of 51 age- and sex-matched individuals without dilation ("controls"). The 3D WSS maps were mapped to a shared geometry where the ascending aorta was divided into 40×40 surface patches. Synthetic data were created and used to assess the false positive and false negative rates for permutation tests with threshold-free cluster enhancement (TFCE) and, for comparison, for statistical tests common in cardiovascular studies, namely the Student's t-test (with and without Bonferroni correction and Benjamin-Hochberg procedure), and the Wilcoxon rank sum test. RESULTS: Significance maps obtained from synthetic data showed that permutation tests had lower false positive rates compared to the uncorrected Student's t-test and the Wilcoxon rank sum test, lower false negative rates compared to the Student's t-test with Bonferroni correction, but higher false negative rates compared to the Student's t-test with the Benjamin-Hochberg procedure. However, the false negatives were concentrated near the boundary of regions of no difference between the groups. On the real data, several regions, indicated as significant by the non-corrected Student's t-test, were not significant when statistical testing was corrected for multiple comparisons. Significance maps created with TFCE-based permutation tests reveal that individuals with mild-to-moderate aortic dilation and tricuspid valves have lower peak WSS, higher OSI, and higher WSS in diastole. CONCLUSION: Permutation tests applied to 4D Flow-derived WSS parameters are suitable for the local analysis of WSS differences between cohorts, correcting for the family-wise error rate while accounting for spatial relationships between WSS values.
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Trenti et al. (2026) studied this question.
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